Leveraging the power of Twitter

Last week I posted the following twitter request — “Can somebody loan me (or buy me) a Dell 2950 decked out so I can run and publish some benchmarks. Please!”

In a same day response I was offered access to use 2 x Dell 1950’s, and today I’m now actually using these machines for my own testing. I would like to thank cafemom (Barry, Anthony & Dan) for the loan of hardware.

And now the chance to better understand the RAID configuration of the DELL PERC Controllers, trying out some different RAID types, LVM configurations and disk tests. When I’m done with my System Administrator refresher, I’m then be trying some different MySQL Benchmarks to test various MySQL configuration settings including using the new Juice benchmark.

Tagged with: Benchmarking Databases General Linux MySQL Twitter

Producing Alternative Means statistics with SQL

Producing Alternative Means statistics with SQL

MySQL’s built-in AVG() computes the arithmetic mean — the sum divided by the count. That is the right default for many questions, but it is not always the right measure of central tendency.

Extending MySQL Capabilities with UDFs, Plugins and Components

Extending MySQL Capabilities with UDFs, Plugins and Components

MySQL offers three different approaches to extending the SQL capabilities with the default product you download and install. These are: User Defined Function (UDF) MySQL Manual MySQL Plugin MySQL Manual MySQL Component MySQL Manual For the purposes of this post I will be using the current LTS version MySQL 8.

Producing One-Sample Z-Test statistics with SQL

Producing One-Sample Z-Test statistics with SQL

The one-sample Z-test determines whether a sample mean differs significantly from a known population mean when the population standard deviation is also known. It is the appropriate test when the population parameters are established — quality control benchmarks, national averages, long-run process measurements — and you want to evaluate whether a new sample is consistent with them.